Ontological Analysis of Outcomes of Non-formal and Informal Learning for Agro-Advisory System AdvisOnt

Abstract

Agricultural advisory systems are widely used now for fast dissemination of agricultural knowledge and information, introduction of modern scientific research and technologies in production, mobility and constant advanced training of agricultural specialists. Their implementation becomes an important factor in competitiveness of rural economy. We consider advisory systems used by various countries and regions, their specifics and aims, and knowledge bases that can be used as bedrock for agro-advisory applications – the European Multilingual Classifier of Skills, Competences, Qualifications and Occupations ESCO ontology, ontologies of learning resources (on example of MOOCs), user profile ontologies. Analyses of the intelligent Web-oriented informational technologies shows an expedience of advisory development based on the Semantic Web standards of knowledge representation and processing. An important factor of advisory efficiency deals with semantic documentation and validation of non-formal and informal learning outcomes typical for agriculture. We propose semantic advisory system AdvisOnt based on ontological representation of knowledge about competencies, vacancies, training courses, user profiles, employers and companies. AdvisOnt services match available vacancies and applicant profiles to recommend employment or further learning of wanting competences by analysis of their formal, non-formal and informal learning outcomes.